Ultrasound Department, The Second Affiliated Hospital, Key Laboratory of Education Ministry for Myocardial Ischemia Mechanism and Treatment, Harbin Medical University, 148 Baojian Road, Harbin 150086, Heilongjiang, China.
Eur J Radiol. 2010 Jul;75(1):e136-41. doi: 10.1016/j.ejrad.2009.10.001. Epub 2009 Nov 12.
To retrospectively evaluate the effects of a speckle reduction algorithm on radiologists' diagnosis of malignant and benign breast lesions on ultrasound (US) images.
Using a database of 603 breast (US) images of 211 cases (109 benign lesions and 102 malignant ones), the original and speckle-reduced images were assessed by five radiologists and final assessment categories were assigned to indicate the probability of malignancy according to BI-RADS-US. The diagnostic sensitivity and specificity were investigated by the areas (Az) under the receiver operating characteristic (ROC) curves.
The sensitivity and specificity of breast lesions on Ultrasound images improved from 88.7% to 94.3%, from 68.6% to 75.2%, respectively, and the area (Az) under ROC curve of diagnosis also increased from 0.843 to 0.939, Z=4.969, there were significant differences in the Az between the original breast lesions and speckle-reduced ones on Ultrasound images (P<0.001). The diagnostic accuracy of breast lesions had been highly improved from 78.67% to 92.73% after employing this algorithm.
The results demonstrate the promising performance of the proposed speckle reduction algorithm in distinguishing malignant from benign breast lesions which will be useful for breast cancer diagnosis.
回顾性评估斑点减少算法对超声（US）图像中良、恶性乳腺病变诊断的影响。
使用 211 例（109 例良性病变和 102 例恶性病变）共 603 例乳腺（US）图像数据库，由 5 位放射科医生对原始图像和斑点减少图像进行评估，并根据 BI-RADS-US 对最终评估类别进行赋值，以指示恶性病变的可能性。通过接收者操作特征（ROC）曲线下的面积（Az）研究诊断的敏感性和特异性。
乳腺病变的超声图像的敏感性和特异性分别从 88.7%提高到 94.3%，从 68.6%提高到 75.2%，诊断 ROC 曲线下的面积（Az）也从 0.843 增加到 0.939，Z=4.969，原始和斑点减少的乳腺病变的 Az 之间存在显著差异（P<0.001）。使用该算法后，乳腺病变的诊断准确性从 78.67%提高到 92.73%。
结果表明，所提出的斑点减少算法在区分良、恶性乳腺病变方面具有良好的性能，有助于乳腺癌的诊断。
